Osteosarcopenic obesity and its components—osteoporosis, sarcopenia, and obesity—are associated with blood cell count-derived inflammation indices in older Chinese people

Nie, Yizhen; Yan, Zhaoqi; Yin, Huiming; Shan, Linghan; Wang, Jiahui; Wu, Qunhong

doi:10.1186/s12877-022-03225-x

Cited by 20 publications

(14 citation statements)

References 71 publications

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“…A number of recent studies have revealed that blood routine examination-derived biomarkers, such as MLR, NLR, and PLR, whose might be closely associated with systemic inflammation and immune response status [ 31 , 32 ]. Due to these composite inflammation indices being calculated from multiple inflammatory cell counts according to the formula, they have the advantages of being easy to measure and relatively stable compared with other inflammatory markers such as IL-6, IL-9 and TNF-α [ 19 , 33 ]. Only peripheral blood samples are required, which almost cause no discomfort.…”

Section: Discussionmentioning

confidence: 99%

“…And these inflammatory markers have been proven to play pivotal roles in the risk and prognosis assessment of ankylosing spondylitis, cardiovascular diseases, and malignant tumors [16][17][18]. In addition, a cross-sectional study of 648 older adults showed that high levels of NLR and PLR were closely correlated with the prevalence of osteoporosis, suggesting that NLR and PLR are potential targets for osteoporosis screening [19]. Similarly, Tang et al reported that systemic immune-inflammation index (SII) and PLR serve as valuable and convenient inflammatory markers that can be used to predict the risk of low BMD or osteoporosis in postmenopausal women [20].…”

Section: Introductionmentioning

confidence: 99%

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Association between inflammatory markers and bone mineral density: a cross-sectional study from NHANES 2007–2010

et al. 2023

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Purpose Monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) are acknowledged as novel inflammatory markers. However, studies investigating the correlation between inflammatory markers and osteoporosis (OP) remain scarce. We aimed to investigate the relationship between NLR, MLR, PLR and bone mineral density (BMD). Methods A total of 9054 participants from the National Health and Nutrition Examination Survey were included in the study. MLR, NLR and PLR were calculated for each patient based on routine blood tests. Given the complex study design and sample weights, the relationship between inflammatory markers and BMD was evaluated through weighted multivariable-adjusted logistic regression and smooth curve fittings. In addition, several subgroup analyses were conducted to assess the robustness of the outcomes. Results This study observed no significant relationship between MLR and lumbar spine BMD (P = 0.604). However, NLR was positively correlated with lumbar spine BMD (β = 0.004, 95% CI: 0.001 to 0.006, P = 0.001) and PLR was negatively linked to lumbar spine BMD (β = − 0.001, 95% CI: − 0.001 to − 0.000, P = 0.002) after accounting for covariates. When bone density measurements were changed to the total femur and femoral neck, PLR was still significantly positively correlated with total femur (β = − 0.001, 95% CI: − 0.001, − 0.000, P = 0.001) and femoral neck BMD (β = − 0.001, 95% CI: − 0.002, − 0.001, P < 0.001). After converting PLR to a categorical variable (quartiles), participants in the highest PLR quartile had a 0.011/cm2 lower BMD than those in the lowest PLR quartile (β = − 0.011, 95% CI: − 0.019, − 0.004, P = 0.005). According to subgroup analyses stratified by gender and age, the negative correlation with PLR and lumbar spine BMD remained in males and age < 18 groups, but not in female and other age groups. Conclusions NLR and PLR were positively and negatively correlated with lumbar BMD, respectively. And PLR might serve as a potential inflammatory predictor of osteoporosis outperforming MLR and NLR. The complex correlation between the inflammation markers and bone metabolism requires further evaluation in large prospective studies.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Association between inflammatory markers and bone mineral density: a cross-sectional study from NHANES 2007–2010

et al. 2023

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“…Chronic inflammation has been identified as a predisposing factor for progressive bone loss [ 8 , 9 ]. People with significantly higher levels of inflammatory cytokines than healthy individuals are more prone to osteoporosis, and accumulation of inflammatory cytokines can mediate oxidative stress injury, promote osteoclast proliferation, and increase bone resorption, leading to osteoporosis [ 10 , 11 ].…”

Section: Discussionmentioning

confidence: 99%

“…Interestingly, relatively high levels of fibrinogen have been found to be associated with lower BMD only in Non-Hispanic White and Mexican American postmenopausal women. This may be related to dietary habits and body fat distribution in different races, especially ectopic and visceral fat [ 9 ]. Some experimental animal studies have found that high-fat diet-induced obesity increases the deleterious effects of estrogen deficiency on bone in a mouse model of postmenopausal women, and that obesity and estrogen deficiency may affect inflammation levels leading to increased bone fragility [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

Association between fibrinogen and bone mineral density in postmenopausal women

Wang

Yan

et al. 2023

J Orthop Surg Res

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Objective There is very limited of evidence linking fibrinogen and bone mineral density (BMD) in postmenopausal women. Therefore, this study intended to examine the relationship between fibrinogen and total BMD in postmenopausal women. Methods This cross-sectional analysis included 2043 postmenopausal women aged 50 years and older from the 1999 to 2002 National Health and Nutrition Examination Survey. The independent variable was fibrinogen and the outcome variable was total BMD. The association between fibrinogen and total BMD in postmenopausal women was examined using multivariate linear regression models, with subgroup analyses stratified by race. Smoothing curve fitting and generalized additive models further analyzed the sample data. Results In multiple regression models adjusted for potential confounders, fibrinogen was negatively associated with total BMD (model 1: − 0.0002 [− 0.0002, − 0.0001], model 2: − 0.0000 [− 0.0001, − 0.0000], model 3: − 0.0001 [− 0.0001, − 0.0001]). In subgroup analysis stratified by race, fibrinogen levels were negatively associated with total BMD in postmenopausal women, Non-Hispanic Whites, and Mexican Americans. However, in Non-Hispanic Blacks, the correlation between fibrinogen levels and total BMD was not significant. For individuals that identify as Other Races, fibrinogen levels were positively correlated with total BMD. Conclusion Our findings show a negative association between fibrinogen levels and total BMD in most postmenopausal women aged 50 years and older, however, is variable by race. In postmenopausal women, Non-Hispanic Whites and Mexican Americans, relatively high fibrinogen levels may be adverse to bone health.

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“…A growing of evidence has reported that inflammation is connected to bone health [ 4 , 5 ]. Several clinical studies revealed that there was inverse relationship between bone mineral density (BMD) and inflammatory markers, including C-reactive protein [ 6 ] and neutrophil lymphocyte ratio [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Relationship between diet-related inflammation and bone health under different levels of body mass index

et al. 2023

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Background Osteoporosis is a major public health problem. Dietary inflammatory preference and body mass index (BMI) are emerging factors that tends to affect bone health. There is limited evidence regarding the joint influence of BMI and dietary status on the bone health. This study aimed to investigate the relationship between dietary inflammatory index (DII) and bone health among adults under different levels of BMI utilizing the National Health and Nutrition Examination Survey (NHANES). Methods Data were collected from 2005–2010, 2013–2014 to 2017–2018 in NHANES. In total, 10,521 participants who aged ≥ 20 years and had complete data for dietary intake interview, bone mineral density (BMD) and bone mineral content (BMC) were included. DII was performed to evaluate the dietary inflammatory potential based on dietary intake interview. We evaluated bone health by femoral neck BMD and BMC measured by dual energy X-ray absorptiometry. Weighted multivariable linear regression and BMI-stratified subgroup analysis were performed. Results The average DII score for 10,521 participants was 1.24 ± 0.04, mean femoral neck BMD was 0.82 ± 0.00 g/cm2 and mean BMC was 4.37 ± 0.01 g. In the fully adjusted model, there was a negative correlation between DII with BMD (β = − 0.016, P < 0.001) and BMC (β = − 0.011, P < 0.001) in the most anti-inflammatory diet. Using BMI-stratified subgroup analysis, this correlation became more evident in both the overweight (BMD: β = − 0.024, P < 0.001; BMC: β = − 0.058, P = 0.042) and obese groups (BMD: β = − 0.015, P = 0.049; BMC: β = − 0.009, P = 0.042), while this correlation was opposite in DII tertile 2 (middle DII score) in the underweight group (BMD: β = 0.047, P = 0.038; BMC: β = 0.274, P = 0.010). Conclusion Relationship between higher consumption of pro-inflammatory and increased risk of lower BMD and BMC was only existed in overweight and obese participants.

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Osteosarcopenic obesity and its components—osteoporosis, sarcopenia, and obesity—are associated with blood cell count-derived inflammation indices in older Chinese people

Cited by 20 publications

References 71 publications

Association between inflammatory markers and bone mineral density: a cross-sectional study from NHANES 2007–2010

Association between inflammatory markers and bone mineral density: a cross-sectional study from NHANES 2007–2010

Association between fibrinogen and bone mineral density in postmenopausal women

Relationship between diet-related inflammation and bone health under different levels of body mass index

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